





"""simple docstring"""





import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


SCREAMING_SNAKE_CASE__   =  "__DUMMY_TRANSFORMERS_USER__"
SCREAMING_SNAKE_CASE__   =  "Dummy User"
SCREAMING_SNAKE_CASE__   =  "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"

SCREAMING_SNAKE_CASE__   =  "https://hub-ci.huggingface.co"
SCREAMING_SNAKE_CASE__   =  CI_HUB_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
SCREAMING_SNAKE_CASE__   =  CI_HUB_ENDPOINT + "/{repo_id}/resolve/{revision}/{filename}"
SCREAMING_SNAKE_CASE__   =  Path("~/.huggingface/hub_ci_token").expanduser()


@pytest.fixture
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		List[str]     ):







      '''simple docstring'''




      monkeypatch.setattr(
          """huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"""				,		SCREAMING_SNAKE_CASE     )


@pytest.fixture
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		int     ):







      '''simple docstring'''




      monkeypatch.setattr("""datasets.config.HF_ENDPOINT"""				,		SCREAMING_SNAKE_CASE     )
      monkeypatch.setattr("""datasets.config.HUB_DATASETS_URL"""				,		SCREAMING_SNAKE_CASE     )


@pytest.fixture
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		int     ):







      '''simple docstring'''




      monkeypatch.setattr("""huggingface_hub.hf_api.HfFolder.path_token"""				,		SCREAMING_SNAKE_CASE     )


@pytest.fixture
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		Dict				,		SCREAMING_SNAKE_CASE	:		Optional[Any]     ):







      '''simple docstring'''




      HfFolder.save_token(SCREAMING_SNAKE_CASE     )
      yield
      HfFolder.delete_token()


@pytest.fixture(scope="""session"""     )
def      UpperCAmelCase__				(    ):







      '''simple docstring'''




      return HfApi(endpoint=SCREAMING_SNAKE_CASE     )


@pytest.fixture(scope="""session"""     )
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		HfApi     ):







      '''simple docstring'''




      lowerCAmelCase    		=			HfFolder.get_token()
      HfFolder.save_token(SCREAMING_SNAKE_CASE     )
      yield CI_HUB_USER_TOKEN
      if previous_token is not None:
            HfFolder.save_token(SCREAMING_SNAKE_CASE     )


@pytest.fixture
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		List[str]     ):







      '''simple docstring'''




      def _cleanup_repo(SCREAMING_SNAKE_CASE	:		str     ):
            hf_api.delete_repo(SCREAMING_SNAKE_CASE				,		token=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""     )

      return _cleanup_repo


@pytest.fixture
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		List[str]     ):







      '''simple docstring'''




      @contextmanager
      def _temporary_repo(SCREAMING_SNAKE_CASE	:		Optional[Any]     ):
            try:
                  yield repo_id
            finally:
                  cleanup_repo(SCREAMING_SNAKE_CASE     )

      return _temporary_repo


@pytest.fixture(scope="""session"""     )
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		HfApi				,		SCREAMING_SNAKE_CASE	:		List[Any]				,		SCREAMING_SNAKE_CASE	:		Optional[int]     ):







      '''simple docstring'''




      lowerCAmelCase    		=			F'repo_txt_data-{int(time.time() * 10e3     )}'
      lowerCAmelCase    		=			F'{CI_HUB_USER}/{repo_name}'
      hf_api.create_repo(SCREAMING_SNAKE_CASE				,		token=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""				,		private=SCREAMING_SNAKE_CASE     )
      hf_api.upload_file(
          token=SCREAMING_SNAKE_CASE				,		path_or_fileobj=str(SCREAMING_SNAKE_CASE     )				,		path_in_repo="""data/text_data.txt"""				,		repo_id=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""				,		)
      yield repo_id
      try:
            hf_api.delete_repo(SCREAMING_SNAKE_CASE				,		token=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""     )
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass


@pytest.fixture()
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		Union[str, Any]				,		SCREAMING_SNAKE_CASE	:		Any				,		SCREAMING_SNAKE_CASE	:		Optional[Any]     ):







      '''simple docstring'''




      return hf_private_dataset_repo_txt_data_


@pytest.fixture(scope="""session"""     )
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		HfApi				,		SCREAMING_SNAKE_CASE	:		int				,		SCREAMING_SNAKE_CASE	:		List[str]     ):







      '''simple docstring'''




      lowerCAmelCase    		=			F'repo_zipped_txt_data-{int(time.time() * 10e3     )}'
      lowerCAmelCase    		=			F'{CI_HUB_USER}/{repo_name}'
      hf_api.create_repo(SCREAMING_SNAKE_CASE				,		token=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""				,		private=SCREAMING_SNAKE_CASE     )
      hf_api.upload_file(
          token=SCREAMING_SNAKE_CASE				,		path_or_fileobj=str(SCREAMING_SNAKE_CASE     )				,		path_in_repo="""data.zip"""				,		repo_id=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""				,		)
      yield repo_id
      try:
            hf_api.delete_repo(SCREAMING_SNAKE_CASE				,		token=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""     )
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass


@pytest.fixture()
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		Optional[Any]				,		SCREAMING_SNAKE_CASE	:		Optional[int]				,		SCREAMING_SNAKE_CASE	:		Optional[Any]     ):







      '''simple docstring'''




      return hf_private_dataset_repo_zipped_txt_data_


@pytest.fixture(scope="""session"""     )
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		HfApi				,		SCREAMING_SNAKE_CASE	:		Optional[int]				,		SCREAMING_SNAKE_CASE	:		Any     ):







      '''simple docstring'''




      lowerCAmelCase    		=			F'repo_zipped_img_data-{int(time.time() * 10e3     )}'
      lowerCAmelCase    		=			F'{CI_HUB_USER}/{repo_name}'
      hf_api.create_repo(SCREAMING_SNAKE_CASE				,		token=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""				,		private=SCREAMING_SNAKE_CASE     )
      hf_api.upload_file(
          token=SCREAMING_SNAKE_CASE				,		path_or_fileobj=str(SCREAMING_SNAKE_CASE     )				,		path_in_repo="""data.zip"""				,		repo_id=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""				,		)
      yield repo_id
      try:
            hf_api.delete_repo(SCREAMING_SNAKE_CASE				,		token=SCREAMING_SNAKE_CASE				,		repo_type="""dataset"""     )
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass






@pytest.fixture()
def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		int				,		SCREAMING_SNAKE_CASE	:		str				,		SCREAMING_SNAKE_CASE	:		int     ):







      '''simple docstring'''




      return hf_private_dataset_repo_zipped_img_data_













"""simple docstring"""





import unittest

import numpy as np
import torch

from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()

class 						lowercase   (   unittest.TestCase   ):





      @property
      def        _snake_case     (			self					)						->	List[str]:
            torch.manual_seed(0					)
            lowerCAmelCase    		=			UNetaDModel(
                block_out_channels=(32, 64) ,		layers_per_block=2 ,		sample_size=32 ,		in_channels=3 ,		out_channels=3 ,		down_block_types=("""DownBlock2D""", """AttnDownBlock2D""") ,		up_block_types=("""AttnUpBlock2D""", """UpBlock2D""") ,		)
            return model





      def        _snake_case     (			self					)						->	List[Any]:
            lowerCAmelCase    		=			self.dummy_uncond_unet
            lowerCAmelCase    		=			ScoreSdeVeScheduler()

            lowerCAmelCase    		=			ScoreSdeVePipeline(unet=lowercase ,		scheduler=lowercase					)
            sde_ve.to(lowercase					)
            sde_ve.set_progress_bar_config(disable=lowercase					)

            lowerCAmelCase    		=			torch.manual_seed(0					)
            lowerCAmelCase    		=			sde_ve(num_inference_steps=2 ,		output_type="""numpy""" ,		generator=lowercase					).images

            lowerCAmelCase    		=			torch.manual_seed(0					)
            lowerCAmelCase    		=			sde_ve(num_inference_steps=2 ,		output_type="""numpy""" ,		generator=lowercase ,		return_dict=lowercase					)[
                0
            ]

            lowerCAmelCase    		=			image[0, -3:, -3:, -1]
            lowerCAmelCase    		=			image_from_tuple[0, -3:, -3:, -1]

            assert image.shape == (1, 32, 32, 3)
            lowerCAmelCase    		=			np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]					)

            assert np.abs(image_slice.flatten() - expected_slice					).max() < 1e-2
            assert np.abs(image_from_tuple_slice.flatten() - expected_slice					).max() < 1e-2







@slow
@require_torch
class 						lowercase   (   unittest.TestCase   ):





      def        _snake_case     (			self					)						->	Optional[int]:
            lowerCAmelCase    		=			"""google/ncsnpp-church-256"""
            lowerCAmelCase    		=			UNetaDModel.from_pretrained(lowercase					)

            lowerCAmelCase    		=			ScoreSdeVeScheduler.from_pretrained(lowercase					)

            lowerCAmelCase    		=			ScoreSdeVePipeline(unet=lowercase ,		scheduler=lowercase					)
            sde_ve.to(lowercase					)
            sde_ve.set_progress_bar_config(disable=lowercase					)

            lowerCAmelCase    		=			torch.manual_seed(0					)
            lowerCAmelCase    		=			sde_ve(num_inference_steps=10 ,		output_type="""numpy""" ,		generator=lowercase					).images

            lowerCAmelCase    		=			image[0, -3:, -3:, -1]

            assert image.shape == (1, 256, 256, 3)

            lowerCAmelCase    		=			np.array([0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0]					)

            assert np.abs(image_slice.flatten() - expected_slice					).max() < 1e-2






